1. Technical Field
The present invention relates to a system and method of improved exercise through rhythmic cuing using sensors for detecting left and right initiated goal directed movement sequences on a foot platform of a cardio-fitness machine, or while seated on an exercise bike and a musical phrase having a grouping of beats whereby sound signals in the musical phrase coincide with light emissions that guide the users movement to be detected.
2. Description of the Related Art
Some games use rhythmic motion to advance the process of a game. Rhythmic motion is also used to rehabilitate those with movement impairment. Rhythmic exercise is currently popular in indoor cycling to music or floor exercises performed in groups settings. Visual sensory stimuli are most commonly used in the performance of these rhythmic tasks. Either a leader or an instructor of some sort guide participants to base their movements on visuals to perform the exercise correctly in time with music. In other forms of conventional exercise, music combines with movement for motivational and distractive purposes only. Popular running and biking activities that use music to exercise to lack the precision movement that develops rhythmic sensorimotor skill. And gesture based gaming exercise known as exergames opt the user to synchronize motion with moving images—not the music per se. As a result exergaming fails to offer participants a system and method for assimilating rhythmic feedback to guide future performances more precisely during exercise. Using goal directed movement patterns on cardio-fitness machines addresses these issues and creates a new form of exercise that stimulates a discovery of sensorimotor acuity beneficial to overall human health.
Recent improvements and cost reductions in contactless movement sensing have brought such technology within reach of consumer products such as video games. 3-D perception is accomplished through devices that sense depth and collect 3-D information in raw form as a collection of points (point cloud) that represents the 3-D space or object. There are various approaches to capturing such information, but the two most accurate are time of light and structured light sensing.
Time of flight sensing involves pulsing infrared light or lasers (invisible to the eye) at the object, measuring the time it takes for the light to return, and computing the distance. The system acquires a 3-D equivalent of an image bitmap, where the collection of points approximates the object. To reduce processing and bandwidth demands an approach known as motion contrast may be used—rescanning only the areas where visual changes are detected. This approach is analogous to video compression techniques, where a video is compressed by storing only the visual changes, thereby requiring less storage and bandwidth.
The structured light approach projects an infrared pattern (invisible to the eye), photographs the pattern through a separate camera, and then calculates distances and angles from the distortions of the pattern. This method provides the appropriate balance of cost and accuracy and can also be packaged in small form factors. One of the first consumer products to use structured light was the Microsoft Kinect sensor for Xbox gaming applications.
Thibaut Weise, Bastian Leibe and Luc Van Gool of the Swiss Federal Institute of Technology (ETH Zurich) have described a 3D scanning system combining stereo and active illumination based on phase-shift for robust and accurate scene reconstruction. Due to the sequential recording of three patterns, motion will introduce artifacts in the reconstruction. A closed-form expression for the motion error is used in order to apply motion compensation on a pixel level. The resulting scanning system can capture accurate depth maps of complex dynamic scenes at 17 fps and can cope with both rigid and deformable objects. Motion Contrast 3D scanning maximizes bandwidth and light source power to avoid performance trade-offs. This technique allows laser scanning resolution with single-shot speed, even in the presence of strong ambient illumination, significant inter-reflections, and highly reflective surfaces. State of the art movement sensors may be used in conjunction with virtual or augmented reality headsets (e.g., Oculus Rift, HTC Vive) to allow users to experience an immersive virtual or augmented reality.